By: Nik Korba
“Is it real music?” When AI-generated music first appeared, that was the question. And it’s a question many still feel hasn’t been adequately answered. Some media reports refer to AI music generators as “fake artists,” while others say the music they are putting out is “absurdly good.”
But as making music with AI has become more common, new questions are being asked. Some involve the artistic side of music, asking, for example, if AI songs have soul. Others point to more practical matters, such as who owns an AI-generated song, who can use it, and whether it is legal to sell it. For those in the music industry, answering the practical questions that deal with commercial use issues feels more urgent.
“AI-generated music isn’t illegal,” says Jared Navarre, Founder of Keyni Consulting and CEO of ONNIX. “Making it isn’t a crime. Uploading it isn’t automatically a violation. Monetizing streams from it isn’t inherently wrong. But the fact that it isn’t illegal doesn’t mean it’s easy to manage.”
Navarre is a multidisciplinary founder and creative strategist with experience launching, scaling, and exiting ventures across IT, logistics, entertainment, and service industries. He has consulted over 250 businesses, specializing in building operational systems, designing resilient technology infrastructure, and developing multi-platform brand ecosystems that resonate with both niche and mainstream audiences. Navarre is also chairman of the humanitarian NGOs IN-Fire and Project AK-47 and the creator of ZILLION, an immersive music project that blends narrative, multimedia, and live performance into a cohesive storytelling experience.
“AI-generated music generally can’t be copyrighted if there’s no meaningful human authorship,” Navarre says. “But copyright governs ownership, not whether money can move. Streaming runs on contracts, platform policies, and payout systems. So even when a track has weak or no copyright protection, it can still be monetized if the platform allows it. That’s the messy part: the law may say one thing about ownership, while the platform economy still pays out.”
How AI Music Generators Went From Making Slop To Making Music
AI-driven music creation has advanced at a breakneck pace. Prior to 2024, few people were using AI to create high-quality music; most were using it to create background music with lo-fi elements for a “cozier” feel. If you were shopping for royalty-free music, you could find AI-generated songs that would get the job done.
But the industry took a huge leap forward in 2024 when platforms like Suno and Udio started becoming popular, giving anyone who completed a prompt the power to create music. Give the AI music platform the vocal style, tempo, and genre you want, and it will generate a song.
As AI became a competent songwriter capable of developing melodies that were difficult to distinguish from those produced by human artists, new questions began to arise. Now, artists and fans alike weren’t questioning whether AI was good at creating songs, but whether it was good enough to disrupt the industry.
At this point, streaming services like Apple Music and Spotify became more vocal on the issue of AI music generation. On the surface, the services were speaking about the difference between using AI to enhance human creativity and using it to replace human artists altogether. But their deeper concerns centered on how they would protect their investment.
“Streaming services and other digital service providers might care about creativity, but they are terrified (or should be) about the gravity of AI creation,” Navarre says. “AI music can scale infinitely. It can make perfect copies that ship instantly. There’s zero friction, no scarcity, and no ‘original.’ So, if a track can be generated once, then it can be lawfully replicated a thousand times under a thousand artist names. You don’t have infringement; you have an arbitrage loop.”
Why Using AI to Create Songs Creates Problems
There was a time when the big concern facing streaming platforms was that AI-powered composing might dilute the quality of their libraries. The fear was that listeners would get fed up with the subpar music and take their subscription money elsewhere.
But as the quality of AI music has increased, that concern feels less troubling. In fact, recent reports indicate that 97% of people can’t tell the difference between songs written by generative AI and those written by humans.
As AI composers start to blend in with their human counterparts, streaming platforms face a new challenge. The platforms were designed to benefit from the limitations of human artists, limitations that AI music generators don’t have.
“The system was built for songs that take time, talent, and cost to create,” Navarre says. “Drop infinite, zero-marginal-cost supply into that model, and the economics start to eat themselves alive. That’s why platforms are taking action, and it has very little to do with legal purity or artistic virtue. Royalty pools are finite, and their recommendation engines reward volume, not copyrights.”
Streaming services are desperately trying to find a response to AI-generated music that works for subscribers, artists, and the platforms’ infrastructure and revenue model. For now, that response is focused primarily on identification. But if authentication efforts don’t fix the revenue model, additional steps will be sure to follow.
“To be clear, the detection of AI-generated songs isn’t about policing art,” Navarre argues. “It’s about preventing a chaos doomsday scenario where unlimited synthetic supply floods the pipes and quietly drains the value of the entire ecosystem. This isn’t copyright enforcement. It’s economic self-defense.”
